Objective To provide references and suggestions for researchers and regulatory authorities in promoting the coordinated development of health, pharmaceutical and medical insurance standardization work. Methods Based on the current standard management policies of health, pharmaceutical and medical insurance industries, the similarities and differences in regulatory, organizational, and technical management systems were compared and some special points were analyzed. Results Relatively complete standard management systems have been established in the health, pharmaceutical medical insurance industries, but there were differences in these systems due to various factors. The pharmaceutical standard regulatory system was the most comprehensive, with national occupational health standards and national drug standards, possessing the status of national standards, issued by industry regulatory authorities, and standard management technical organizations could be established by them. Standardization work in the medical insurance industry was still in its infancy, and there was considerable room for improvement in the standard management system. Conclusion In order to promote the development of the medical and health system, it is suggested to optimize the medical and pharmaceutical standard technology system, improve the construction of medical device standard regulatory system, accelerate the construction of the medical insurance standard management system, and establish the joint working mechanism for health, pharmaceutical and medical insurance.

Objective To investigate the influence of standard single fiber on the luminous flux test results of endoscope cold light sources. Methods The same endoscopic LED cold light source was tested successively as follows: select four standard single optical fibers with different numerical apertures for comparative testing of total luminous flux, select three standard single optical fibers using the same method for measuring luminous energy transfer efficiency for comparative testing of total luminous flux, and conduct comparative testing of spot size after coupling the cold light source with standard single optical fibers/optical cables. By calculating the standard deviation of multiple test stability, and analyzing the relative deviation range of different optical fiber test results in comparative testing, the influence of numerical aperture, light energy transfer efficiency, and fiber coupling on the total luminous flux test results of standard single optical fibers was analyzed. Results The standard deviation obtained from repeated tests of the four standard single optical fibers did not exceed 1% of the measured value, indicating good stability of the test system itself. The relative deviation of the test results of the standard single optical fibers with numerical apertures ranging from 0.36 to 0.64 was -9.28% to +6.89%. Similarly, the relative deviation of the test results of three different standard single optical fibers measured by visible laser for light energy transmission efficiency reached -5.66% to +8.30%, both showing relatively large deviations. Additionally, the coupling efficiency between the cold light source and the standard single optical fiber/matching optical cable was also different, indicating that the standard single optical fiber couldn’t completely replace the optical cable provided with the cold light source equipment for simulation experiments. Conclusion By analyzing the influence of standard single optical fiber parameters on the luminous flux test results of endoscopic cold light sources, it is found that the non-uniqueness of numerical aperture specifications directly affects the test results of total luminous flux, and there are certain differences between the parameters of standard single optical fibers specified in the standards and the actual optical cables used in endoscopic systems. In order to improve the level of quality control and practical significance of testing, it is recommended that standard single optical fibers are no longer used in total luminous flux testing, but instead standard cables approved by manufacturers are directly tested after being adapted.

Objective To explore the impact of different acquisition energy window widths on the quality and quantitative accuracy of single photon emission computed tomography (SPECT) images. Methods Using the NEMA/IEC quality control model, six small balls and a phantom cavity were perfused with 320 and 10 kBq/mL 99mTcO4 - solution (sphere background ratio of 32∶1), with a main energy peak of 140 keV and window widths of 5%, 10%, 15%, and 20%, respectively. The maximum uptake value and average radiometer value of different diameter small balls were measured, and the same volume of region of interest was copied in the background area next to the hot ball. The average radiometer count value and standard deviation of the background were automatically measured. The coefficient of variation (CV) of the background, the Contrast between balls and backgrounds, the recovery coefficient, and absolute error were calculated, and quantitatively evaluation of the images was performed. Results As the diameter of each small ball increased, the CV values and Contrast of each small ball gradually increased. The CV value was significantly higher than the other three groups under the 5% window width collection condition, and the differences between 5% and 10%, 5% and 15%, and 5% and 20% were statistically significant (P<0.05), while there was no statistically significant difference in pairwise comparison between the other groups (P>0.05). The Contrast decreased with the increase of acquisition window width, and the overall difference was statistically significant (F=15.730, P<0.05). The overall difference in the recovery coefficients obtained under four different window width collection conditions was statistically significant (F=10.670, P<0.05). The average recovery coefficient obtained was highest at 20% window width, followed by 15% window width, and lowest at 5% window width. The overall difference in absolute error obtained under four collection conditions was statistically significant (F=11.370, P<0.05). The average absolute error obtained was the smallest at 15% window width, followed by 10% window width, and the largest at 5% window width. Conclusion The acquisition of different window widths can have an impact on the quality and quantitative accuracy of SPECT images. The CV value of images collected with a 15% window width is relatively small, the Contrast is high, the radioactive concentration ratio is close to the true value, and the absolute error is the smallest, which is recommended for clinical collection.

Objective To develop an artificial intelligence-assisted system based on the single-stage detection framework of the YOLOv8 network, aiming at automatically detecting images of 11 types of small intestine lesions captured by capsule endoscopy (CE). Methods An image dataset from three different brands of capsule endoscopy devices was utilized for the training and testing of the deep learning model, comprising 13683 images and 24416 annotation labels. The performance of the model was evaluated by accuracy, sensitivity, specificity, false positive rate, and detection speed. Results When evaluating a test set containing 2729 CE images (a total of 4801 annotation labels), the YOLOv8m version demonstrated high precision and faster inference speeds, exhibiting superior performance compared to other versions of YOLO. Specifically, the overall accuracy of YOLOv8m across all categories was 0.9597, with a sensitivity of 0.8176. Among the 11 categories, the “bleeding” category had the highest sensitivity at 0.9342, while the “erythema” category had the lowest sensitivity at 0.6832. In terms of processing speed, YOLOv8m took a total of 16.37 seconds to process 2729 images. Conclusion The AI model based on the YOLOv8m network can swiftly and precisely detect and classify various small intestine lesions, demonstrating significant potential for assisting endoscopists in enhancing the efficiency and accuracy of CE diagnoses.

Objective To propose a dual-task self-supervised learning method, which uses unlabeled medical imaging data to extract general visual representations, aiming to enhance the precise segmentation capabilities of deep learning models in cranial CT scans (including cerebral hemorrhage, nasopharyngeal carcinoma, and routine scans). Methods Combined with image reconstruction and classification as auxiliary tasks, under the condition of 70% image information was occluded, a lightweight feature fusion mechanism between tasks was used to optimize the output representation of pre-training. To evaluate the effectiveness of this method, the average Dice coefficient (mDice) and Hausdorff Distance 95% (HD95) were used as evaluation indexes. After the pre-training process of the self-supervised method, the performance of the downstream brain tissue segmentation model was observed. Results Experimental results demonstrated that the proposed method effectively improved the performance of different deep learning models in segmentation tasks. In a standalone supervised learning environment, ConvNeXt-V2-Base achieved the highest mDice value of 0.8812, while the segmentation method performed optimally in terms of HD95 index of 7.95. Compared to the MAE method, the introduction of the self-supervised pre-training strategy resulted in the best mDice (0.9589) and HD95 (7.10) outcomes for our segmentation method. Additionally, a significant improvement was observed in the segmentation performance of DenseNet121_Backbone, with the mDice metric increasing to 0.9512. Conclusion The self-supervised pre-training method and encoder model exhibit certain advantages in representation learning within CT imaging data, effectively enhancing the model performance for downstream brain tissue segmentation tasks.

Objective Based on ultrasound imaging technology, to propose a kidney disease detection technique using the YOLO object detection model to quickly and effectively detect kidney diseases, improving the detection performance of ultrasound images. Methods The convolution was combined with YOLO in the same training framework and a fused DYOLO model was built in this research. Considering the limitations of traditional convolution specificity, a spatial transformation model was used to improve the model. At the same time, the CSPDarknet53 module was introduced to extract image features, thus achieving automatic adjustment and recognition of kidney shape and size. Results In the comparative effectiveness analysis of pathological images, the image sampling accuracy of the convolution model, YOLOv3 model, YOLOv4 model, and improved DYOLO model were 68.65%, 82.65%, 90.65%, and 95.65%, respectively. In complex kidney data testing, the improved DYOLO model converged after 600 iterations, with an optimal mean average precision of 95.23%, demonstrating the best performance. Conclusion The improved DYOLO model has excellent pathological feature detection capabilities, which is of significant reference value for the detection of kidney diseases.

Objective To compare the dosimetric differences between personalized oral filling and oral stents used in radiotherapy for oropharyngeal cancer. Methods The imaging data of 19 patients with oropharyngeal cancer admitted to the radiotherapy department of our hospital was selected as research objects. All patients were conducted oral stent fixation during simulated positioning. The target area and normal tissue were delineated on the localization CT image, and the original treatment plan (Plan0) was implemented using volumetric modulated radiotherapy. The cavity area containing the stent in the oral cavity was delineated separately on the planned CT, and the mean value was assigned to achieve density filling. The original planned dose was recalculated and saved as Plan1. The D2% (dose received by 2% of the target volume, and so on), D50%, and D98% of the gross target volume (GTV) in two plans were compared, as well as D2%, D50%, D98%, V5 (volume percentage of organs receiving at least 5 Gy dose, and so on), V10, V15, V20, V25, V30, V35, V40, V45, V50, V55, V60 in the oral and air cavity areas; Dmax (maximum dose), Dmean (average dose), and Dmin (minimum dose) of the tip, middle, base of tongue, and left and right parotid glands. And the correlation between oral dose parameters and exposure dose to the tongue and parotid gland was analyzed. Results The D98% (P=0.016) of GTV, Dmin (P=0.038) of the tongue tip, Dmax (P=0.046) of the left parotid gland, and Dmean (P=0.019) of the right parotid gland in the simulated personalized oral filling group all decreased. At the same time, D50%, D98%, V15, V20, V25, V35, V40 and V45 in the oral cavity of Plan1 all decreased. And the evaluation indicators D50%, D98%, V15, V20, V25, V30, V35, V40 and V45 of the intraoral cavity area were also decreased compared with the oral stent group, and all the difference was statistically significant (P<0.05). According to correlation analysis, V15, V20, V25, V30, V35, V40 and V45 in the oral cavity were positively correlated with Dmean and Dmin of the entire tongue (P<0.05). Meanwhile, V15, V30, V35, V40 and V45 were all positively correlated with the Dmax of the tip of tongue, in addition, V35 and V40 were also positively correlated with the Dmax of the middle of tongue (P<0.05). The V15, V20, V25, V30, V35, V40 and V45 in the air cavity area were positively correlated with the Dmean of the tip of tongue, and except for V15, they were positively correlated with the Dmax of the tip of tongue. And V20, 研究论著 RESEARCH WORK 42 中国医疗设备 2025年第40卷 01期  VOL.40 No.01 引言 头颈部恶性肿瘤是常见的恶性肿瘤之一，具有ԧ病 率高和死亡率高的特点。由于头颈部解剖结构较特殊， 使得放疗在其治疗方案中占据重要地位 [1]。据统计，我 国的口咽癌ԧ病率约为每 10 万人中有 4 人ԧ病，在所 有癌症中位居第 20 位 [2]。随着放疗技术的进步，头颈 部肿瘤的治疗效果也越来越好，早中期口咽癌 5 年总生 存率已大于 50%[3]，但放射性口腔黏膜炎（Radiotherapy Induced Oral Mucositis，RIOM）的ԧ生率和严重程度却 未见明显改善 [4]。RIOM ԧ生率高达 80% 以上，其中 3~4 级ԧ生率大于 50%[5]。因此，寻找一种实用的临床方 法以减轻放疗相关不良反应仍然需要探索。口腔支架能 够强制患者在放疗期间处于张口状态，增加口腔黏膜和 舌等危及器官到靶区之间的距离，实现降低危及器官受 照剂量 - 体积、减轻放疗相关不良反应的目的。有研 究通过应用 3D 打印或印模技术设计不同个体化口腔支 架，来降低头颈部恶性肿瘤患者放疗的口腔毒副反 应 [6-7]。由于口腔接触性疼痛使得部分患者在放置口腔 支架时可能伴随支架位置偏移，而常规口腔支架并不 能完全填充口腔，因此在无图像引导情况下难以监测 口腔支架在患者口内的实际位置，且国外相关研究ԧ 现头颈部恶性肿瘤患者放疗时气腔边缘的剂量分布和 剂量波动变化明显 [8]。因此，本研究拟通过计划系统 对比分析放疗期间使用个体化均匀填充和常规口腔支 架 2 组口咽癌患者的靶区和正常组织剂量分布，探讨 个体化口腔填充在临床上的应用价值。 1 资料与方法 1.1 一般资料 回顾性收集 2023 年 6 月至 2024 年 7 月于南京医科 大学第一附属医院放射治疗科接受放疗的口咽癌患者资 料。患者原ԧ灶均经病理学证实，入院 Karnofsky 功能 状态评分≥ 80 分，临床分期（cTNM）为 cT1-4N0-3M0。最 终入组 19 例患者，其中男性 16 例，女性 3 例，年龄范 围为 45~70 岁。研究已经本院伦理委员会审批通过（批 准文号 ：2024-SR-771）。 1.2 模拟定位 常规个性化口腔支架制作过程如下：由同一位放疗医 师根据患者口腔情况进行个性化口腔支架设计，将压舌板 裁剪成不同长度并叠加呈梯形以适配口腔内轮廓 ；口腔支 架的最大厚度为患者最大张口角度时上下门齿间距的 2/3 ； 调整支架的厚度和长度以满足患者张口位，同时患者无咽 部异物感及恶心体征 ；患者试戴后，标记上下齿痕位置； 采用 S- 头颈肩热塑膜 +Cvico 头颈肩底板进行体位固定 ； 应用三维激光灯确定定位中心并以铅点标记 ；使用西门 子大孔径 CT 模拟机完成定位扫描，扫描范围为由颅顶至 气管隆嵴，层厚 3 mm。CT 定位图像通过放疗网络传至 Monaco 5.1 放疗计划系统。 1.3 靶区及危及器官勾画 由同一位主任医师按照口咽癌勾画指南勾画靶区。 肿瘤靶区包括大体肿瘤靶区（Gross Tumor Volume of Nasopharyngeal Carcinoma，GTVnx）和咽后及颈部肿 瘤 靶 区（Gross Tumor Volume of Cervix Node，GTVnd）。 GTVnx 在三维方向上均匀外放 3 mm 后得到计划大体肿 瘤靶区（PGTVnx）；计划颈部肿瘤靶区（PGTVnd）由 GTVnd 外扩 3 mm 得到 ；PTV1、PTV2 分别由高危亚临床 病灶（CTV1）和低危亚临床病灶（CTV2）外放 5 mm 得到。 应用自动勾画技术结合手动调整完成危及器官口腔、舌 和口内气腔的勾画，勾画标准参考相关文献的定义，其 中口腔勾画范围包括披覆于上下唇、硬腭、软腭、口颊、 牙龈、舌和口底等口腔解剖结构的黏膜，以及舌 下腺腺体 [9]。 在正中矢状面图像上，根据舌的最长前 后径将舌平均分为前、中、后 3 个部分，并分别命名为 舌 尖（Tip of Tongue，TOT）、 舌 体（Middle of Tongue， MOT）和舌根（Base of Tongue，BOT）[7]。口内气腔区 为口腔内舌面、下颚向上至上颚（包含口腔支架在口腔 以内的部分），见图 1。 收稿日期：2024-07-30 基金项目：国家自然科学基金（82102831）。 通信作者：王沛沛，副主任技师，主要研究方向为肿瘤放疗物理学。 通信作者邮箱：wangpeipei5650@163.com V25, V30, V35 and V40 also showed a positive correlation with Dmin at the tip of tongue (P<0.05). The remaining differences were not statistically significant (P>0.05). Conclusion Personalized oral filling is beneficial for reducing oral radiation dose in patients with oropharyngeal cancer undergoing intensity modulated radiation therapy.

Objective Based on cone beam CT (CBCT) images, to compare the positioning errors between the head-neck-shoulder combined with abdomen thermoplastic membrane fixation method and the breast bracket fixation method, and study the clinical applicability of head-neck-shoulder combined with abdomen thermoplastic membrane fixed in intensity modulated radiotherapy (IMRT) for patients with breast cancer. Methods A total of 40 patients with breast cancer receiving IMRT were selected. All patients were randomly divided into head-neck-shoulder combined with abdomen thermoplastic membrane fixed group (20 cases) and breast bracket group (20 cases). Before radiotherapy, each patient was scanned by CBCT once a week. The positioning errors, inter-fraction displacement and positioning efficiency of two groups in the X (left-right), Y (in-out), and Z (front-back) directions were analyzed. Results The positioning errors of the head-neck-shoulder combined with abdomen thermoplastic membrane fixed group and the breast bracket group in the direction of X, Y, and Z were as follows: (1.97±0.94) and (2.11±1.55) mm, (2.54±0.57) and (2.82±1.46) mm, (1.27±0.62) and (2.28±0.96) mm, (P=0.801, 0.604, 0.013). The inter-fraction displacement errors were (0.76±0.50) and (1.24±0.52) mm, (1.34±0.15) and (2.52±1.18) mm, (0.73±0.33) and (0.88±0.53) mm, (P=0.453, 0.296, 0.773). The positioning time was (6.5±1.7) and (8.7±3.1) min (P=0.485). The pass rates for the first positioning in the X, Y, and Z directions in the two groups were 90% and 85%, 80% and 70%, 100% and 95% (P=0.632, 0.464, 0.235) and the pass rates for the inter-fraction positioning were 92% and 82%, 88% and 79%, 94% and 88% (P=0.036, 0.086, 0.138). Conclusion In the IMRT for breast cancer, the head-neck-shoulder combined with abdomen thermoplastic membrane fixed technique is simpler and easier to implement, which can control the positioning errors and inter-fraction radiotherapy displacements to a certain extent, especially in the positioning errors in the Z direction, meanwhile improve the positioning efficiency.

Objective To construct a multi-output model based on XGBoost algorithm to predict the dose of bladder and rectum in volumetric modulated arc therapy for cervical cancer. Methods A total of 120 patients who received volumetric modulated arc therapy for cervical cancer in our hospital were selected as research objects. Twenty patients were randomly selected as the test set, while the remaining 100 patients data were divided into a training set using a 4∶1 ratio and subjected to five-fold cross-validation to construct an XGBoost prediction model. The distance to target histogram information of bladder and rectum structures in all patients’ CT scans and the dose drop-off function f(x) in the plan were used as input to extract bladder and rectum differential dose volume histograms. These histograms were discretized at 2 Gy intervals to create multiple dose endpoints (DEs) as outputs, forming a multi-output model. The model’s predictions’ DEs were evaluated against clinical actual values using mean absolute error (MAE) and root mean square error (RMSE) to measure the differences. The dose volume percentage (VRx) was used to compare the model’s predicted cumulative dose volume histogram (cDVH) curves with clinical cDVH curves to assess differences. Results For the rectum dose volume histogram (DVH) curve, the MAE value of all DEs was 0.0206 and the RMSE value of all DEs was 0.0287. For bladder DVH curve, the MAE value of the DEs was 0.0339 and the RMSE value of the DEs was 0.0450. Comparing predicted values with clinical actual values using VRx, approximately 91.8% of bladder predicted values had differences within a 5% error range compared to actual values. For the rectum, the percentage of predicted values within a 5% error range compared to actual values was 94.0%. Furthermore, the model’s DVH prediction performance was better for bladder volumes <500 mL, while it needed improvement for bladder volumes >500 mL. For rectum, the DVH models exhibited excellent performance in different volume. Conclusion A novel multi-output model based on XGBoost required less GPU performance and can optimization process quickly and help medical physicist rapidly assess of dosimetry of rectum and bladder. It provides a new method in the application of radiotherapy by machine learning.

Objective To design a paperless office platform for medical process based on intelligent medical record archiving system, in order to achieve paperless office of medical process. Methods Taking a grade Ⅲ-A hospital as an example, based on information systems such as laboratory information system, hospital information system and picture archiving and communication system, etc., the digital certificate authentication system, information integration platform, medical record quality control system, medical record database and index library, data disaster backup system were designed. On the basis of the “Medical Record Trusted Archiving System V1.0” software, an AI full medical record quality control system was introduced and upgraded to the “Medical Record Trusted Archiving System V2.0”. A paperless office management mechanism was established to achieve intelligent management of the whole life cycle of medical records. Results After the application of the medical process paperless office platform based on the intelligent medical record archiving system, the filing rate of medical records within 7 d increased from 72.66% to 96.87%, and the proportion of Class A medical records increased from 97.74% to 99.14%, and the differences were statistically significant (P<0.001). With the help of a paperless office platform, the average time for querying medical records has been reduced by 157.56 s, and the number of paperless medical records retrieved has also significantly increased; the timely disposal rate within 30 min of the critical value increased from 78.58% to 88.86%, and the differences were statistically significant (P<0.001). The hospital saved approximately 4.96 million yuan in economic costs annually. Conclusion The application of the medical process paperless office platform based on intelligent medical record archiving system has effectively improved the level of hospital medical record archiving and medical process paperless. The hospital has achieved efficient management and utilization of medical records, fully leverages the advantages of paperless management, improves work efficiency, enhances patient experience, and enables medical records to better serve healthcare.

Objective To address the issues encountered by hospitals in the process of patients with handling chronic disease declaration under the background of medical insurance system reform, to improve the efficiency and quality of medical insurance chronic disease audit services, and build a smart service-oriented hospitals. Methods The hospital chronic disease declaration and audit system was based on B/S architecture, integrating WeChat mini-program to achieve online declaration and multi-level audit, with instant feedback provided. Data from three months before and after the system launch were collected and analyzed to assess the application effects of the system. Results After the system was launched, the number of daily transactions was significantly increased (P<0.05). The total time spent on travel willingness, total cost of photocopying documents, total time to complete all procedures and average time to prepare proof materials by a single patient were significantly reduced compared with that before the system was launched (P<0.05). Conclusion The chronic disease declaration and audit system supplements quantitative evidence for the application of informatization in medical insurance services and provides data support for future technology integration and policy-making, which can provide references for innovation in the medical insurance service system.

Objective To optimize the allocation of medical resources, improve service efficiency, solve the problems of primary medical institutions in puncture biopsy interventional surgery due to the distance, weather barrier, time conflict and other reasons can not receive the consultation and implementation from high-level experts, to bring positive social and economic benefits for the medical institutions. Methods Taking a provincial grade Ⅲ-A hospital as an example, combined with the business characteristics of remote interventional surgery, the system was designed by using the micro-service architecture, and the information system that met the actual needs of remote medical collaboration among multiple hospitals was constructed by using distributed development. The puncture effect was verified by using the 3D simulation body model combined with the simulation of physiological movements, such as blood flow and respiration, to carry out the simulation test. Results Based on the trusted network, the platform provided efficient and stable video communication and file transmission, 3D reconstruction and display, puncture path synchronization and other modular mechanisms. Statistically, for the three groups of trajectories with different lengths, the average angular error (AE), target positioning error (TPE), lateral error and first success rate (FSR) were 1.20°±0.71°, (2.35±1.01) mm, (1.85±1.17) mm and 43%, respectively. The hospital successfully carried out 5 cases of remote CT-guided cross-subdivided area biopsy of retroperitoneal masses or lung mass detection puncture with the aid of the system, with the AE<1° and the TPE<1 mm. Conclusion The platform builds a new collaborative scenario, breaks the geographical limitation, and its puncture effect has the basis of clinical application, which can effectively improve the efficiency and quality of interventional surgery diagnosis and treatment. It can provide a template for the telemedicine practice of the domestic healthcare institutions in the field of intervention.

Objective To develop a collaborative decision-making system for medical equipment procurement plans based on the current situation and shortcomings of medical institutions in formulating annual medical equipment procurement plans. Methods By analyzing the shortcomings in the current procurement plan formulation process and combining with the hospital’s demand research, the decision-making system that combines multi department collaborative argumentation with expert committee final review was established. Based on the B/S architecture and model-view-controller (MVC) development mode, the medical equipment procurement plan collaborative decision-making system was developed. The whole process information management of procurement plan application, argumentation, approval and decision-making was achieved. Results After the system was launched, the application and approval time were significantly reduced and the completeness rate of application content filling was effectively improved, with statistically significant (P<0.05). Conclusion The application of this system has promoted the scientific, standardized, efficient and transparent development of medical equipment procurement plans. It has a promoting effect on improving approval efficiency and filling quality, which is of great significance to the healthy development of hospital.

Objective To address the issues of low degree of informatization and the lack of unified closed-loop management system for the outpatient surgery process in hospital, to improve patient treatment efficiency and enhance the work productivity of medical staff. Methods The business requirements of outpatient surgery was analyzed in depth, and the integrated outpatient surgery management system was designed. The system was adopted modularization and microservice architecture, and integrated cutting-edge development technology to organically integrate various links such as surgery appointment, scheduling, preoperative preparation, intraoperative recording, and revenue enhancement, forming a closed-loop management. The functional modules of the system including surgery appointment, project review, clerical recording, revenue enhancement and query statistics were realized. Results The introduction of this system had significantly enhanced the efficiency of outpatient surgeries. The average patient consultation time decreased from (12.82±0.88) min to (10.97±0.53) min, and the rate of missed charges for additional surgical consumables was reduced from 13.22% to 5.86%, with statistical significances (P<0.05). Conclusion The system can meet the work needs of outpatient surgery medical staff in outpatient surgery, which can improve the work efficiency of medical staff, the efficiency of outpatient visits, and the satisfaction of patients.

Objective To optimize the emergency enhanced CT diagnosis and treatment process based on service chain theory, and improve the efficiency of patients’ medical treatment. Methods Based on the service chain theory, the existing problems in the diagnosis and treatment process of emergency enhanced CT of radiology in the case hospital were deeply analyzed, and the improvement measures and optimization plans were put forward. A total of 144 patients before the hospital process optimization (January 2022 to January 2023) were taken as the control group, and 359 patients after the process optimization (February to October 2023) were taken as the observation group. The waiting time and satisfaction of patients in the two groups were compared. Results Through the development and implementation of corresponding improvement measures in the early, middle and later stages of service, after controlling for patient gender, age and examination site variables, the waiting time of patients with emergency enhanced CT decreased from (1.38±0.93) h before optimization to (0.94±0.42) h after optimization, and patient satisfaction increased from 60.42% to 84.12%, and both differences were statistical significant (P<0.001). Conclusion In multi-district hospital, the optimization of emergency enhanced CT diagnosis and treatment process based on service chain theory can continuously and effectively optimize the patients’ medical treatment process, shorten the waiting time of patients and improve the efficiency of medical service.

Objective To explore the effect of failure mode and effects analysis (FMEA) theory combined with find-organizeclarify-understand-select-plan-do-check-act (FOCUS-PDCA) model on the management quality of reusable medical devices in central sterile supply department. Methods The 4562 surgical instruments managed by routine cleaning and disinfection management mode in our hospital from January to April 2023 were taken as the control group, and the 5628 surgical instruments managed by FMEA theory combined with FOCUS-PDCA model from May to August 2023 were taken as the observation group. The failure modes in the management process were identified by applying FMEA theory. The FOCUS-PDCA model was used to continuously make targeted improvements. And the differences in the instrument management failure rate, loss and damage rate, environmental hygiene detection, team cooperation, use satisfaction and incidence of nosocomial infection between the two groups were investigated. Results The instrument management failure rate and loss and damage rate of the observation group were significantly lower than those of the control group, the environmental hygiene detection, team cooperation and satisfaction with the use of surgical instruments were significantly better than those of the control group, and the incidence of nosocomial infection was significantly lower than that of the control group, all differences were statistical significance (P<0.05). Conclusion FMEA theory combined with the FOCUS-PDCA model can significantly improve the cleaning quality of reusable medical devices in central sterile supply department, significantly improve the environmental hygiene of the central sterile supply department, and also improve the teamwork ability between the staff of the central sterile supply department and the doctors’ satisfaction with the medical devices, and reduce the incidence of nosocomial infections.

Objective To analyze the factors influencing the quantity of clinical engineering personnel allocation, and to construct a mathematical model for the quantity of clinical engineering personnel allocation. Methods Based on the Annual Baseline Questionnaire of Shanghai Medical Device Management Quality Control Center in 2021, Stata 15.0 was applied to collate and analyze the data, and explore the statistical relationship between the quantity of clinical engineering personnel and the establishment of procurement centers, outsourcing or not of business, number of hospital beds, hospital grade and total assets of medical equipment, etc. The least square method was used to construct a multiple regression model, and the posterior analysis was carried out on the model. Results Spearman correlation analysis showed that the quantity of clinical engineering personnel was correlated with the number of hospital beds (r=0.7665, P<0.05), hospital grade (r=0.5942, P<0.05), and outsourcing or not of business (r=-0.2924, P<0.05). The coefficient of determination R2 was 0.6229, indicating a good fit of the model. In the posterior analysis, the model had no multicollinearity (VIF=1.74<5) and no obvious outliers (Dmax=0.394<0.5), the residuals had no autocorrelation (d=1.936>du, du=1.73), and the residuals were normally distributed (P=0.199>0.05), and satisfied the homogeneity of variance. Therefore, this multiple regression model had statistical significance. Conclusion There are three variables affecting the quantity of clinical engineering personnel in Shanghai, including the number of hospital beds, hospital grade and outsourcing or not of business. The number of hospital beds and hospital grade are positively correlated with the quantity of clinical engineering personnel, while outsourcing not of business is negatively correlated with the quantity of clinical engineering personnel. The regression model constructed in this study can provide reference for the quantity allocation of clinical engineering personnel in various medical institutions.

Objective To research the main effectiveness evaluation functions of injection pumps based on real world data (RWD) to reflect their true performance in clinical practice, so as to establish a scientific and effective evaluation method. Methods A total of 37 injection pumps of 3 brands (M, F, L) in ICU of our hospital were selected as the research objects. According to the established clinical use evaluation indicators, the time of the first drop and response time of the injection pump were obtained at 3 flow rates of 5, 25 and 50 mL/h, respectively, to test the difference in the quick start performance of the injection pump. The average flow rate, relative indication error and indication repeatability were calculated to test the difference of injection precision. At 3 flow rates of 5, 10 and 15 mL/h, the flow rate fluctuation limit and interval time of the injection pump were obtained to test the performance difference of the automated relay of the injection pump. Results In terms of quick start function, the higher the set flow rate, the shorter the time and response time of the first drop of the injection pump, and the time and response time of the first drop of the injection pump of brand M were the fastest under the three flow rates (P<0.05). In terms of injection precision function, the flow rate control performance and indication stability of brands M and L were significantly better than brand F at the three flow rates (P<0.05). In terms of automated relay function, the lower limit of flow velocity fluctuation and interval time caused by artificial simulation of automated relay function were significantly different (P<0.05), and the higher the set flow rate, the shorter interval time was required for real-time flow rate to recover from the drop to the set value. In addition, the automated relay function of brand M could effectively solve the drug flow jitter or discontinuity generated during the relay process of the pre-sequence pump and the post-sequence pump, but there was an instantaneous flow rate rise, which could relatively ensure the stability and continuity of the drug flow. Conclusion The correct evaluation method for clinical use of injection pumps based on RWD can not only standardize clinical application behavior, but also provide data support for evaluation, admission/elimination, and centralized procurement/price negotiation of injection pumps.

Objective To evaluate the clinical use of hemodialysis equipment through the real world data research method, so as to build an effective evaluation system of hemodialysis equipment. Methods Literature analysis, brainstorming and thematic group discussion were used to determine the evaluation dimension of hemodialysis equipment, key indicators were selected based on the empowerment method and expert scoring method, and patients were selected for randomized group experiments to explore the advantages and disadvantages of different hemodialysis equipment models. Results The evaluation system of hemodialysis equipment centered on four dimensions of treatment, treatment effect, stability and economics in hemodialysis process was established. According to statistics, the treatment score of model B was higher than that of model A (20.90 scores vs. 20.75 scores). The therapeutic effect score of model A was higher than that of model B (13.85 scores vs. 13.39 scores). The stability score of model A was higher than that of model B (23.27 scores vs. 17.25 scores). The economics score of model A was higher than that of model B (20.60 scores vs. 12.29 scores). The purchase price of model A was lower than that of model B (140000 yuan vs. 149000 yuan). The score to original value ratio of model A was higher than that of model B (5.61 scores vs. 4.28 scores). The two models had great differences in stability evaluation and economic evaluation scores, and there were significant differences in some indicators (P<0.05). Conclusion The method used in this study of constructing the evaluation index system of clinical use of hemodialysis equipment is scientific and reasonable, and the constructed index system is comprehensive, objective, focused and practical, which can provide reference for the promotion and application of the index system and the development and management of hemodialysis equipment in the future.

Objective To achieve intelligent management and rapid deployment and sharing of life first-aid equipment based on digital management and Internet of Things monitoring technology. Methods The 5G Internet of Things, AI algorithm, big data, mobile internet and other technologies were used to establish the hardware of the Internet of Things. The semi supervised learning algorithm based on pattern recognition and traditional machine learning was used to monitor the daily status of equipment through equipment operation, standby and shutdown tests, and to calculate the utilization rate, idle rate and other indicators of hospital related equipment, so as to achieve intelligent management and scheduling of medical equipment resources. Taking ventilator, micro-injection pump and monitor of our hospital as the research object, the deployment speed and use time in traditional mode and the Internet of Things monitoring mode were compared and analyzed. Results By applying the Internet of Things monitoring mode, the deployment time of the three types of life first-aid equipment were reduced by more than 80%, and the use time were increased by more than 15%, and the differences were statistically significant (P<0.001). Taking ventilators as an example, in the Internet of Things monitoring mode, the idle deployment speed of ventilators increased by about 85% compared with the traditional mode, the emergency deployment speed increased by about 70%, and the simulated large-scale public health event speed increased by about 49%, and the differences were statistically significant (P<0.001). Conclusion Through 5G Internet of Things and digital management and other technologies, it can realize the fine management of life first-aid equipment, grasp the location, availability, failure rate and other data of the equipment in real time, and enable management personnel to allocate medical resources more reasonably in response to emergency deployment.

Objective To explore the application effect of 6S management combined with 5G smart hospital logistics mode in the management of medical consumables secondary warehouse of clinical nursing unit. Methods The management method of 6S management combined with 5G smart hospital logistics was used to implement a new management mode of medical consumables supported by the Internet of Things. The application effect of the new medical consumables management process was verified by comparing the optimization of the human resources and work efficiency and average patient costs from January to June 2023 to July to December 2022. Results Through the implementation of 6S management combined with 5G smart hospital logistics mode, the average weekly delivery frequency of 97 nursing units in our hospital was reduced from 2.50 times to 1.69 times. Weekly supplier deliveries decreased from 122.92 to 80.58. The average weekly acceptance time decreased from 21.46 h to 8.08 h. And all the differences were statistically significant (P<0.05). At the same time, the average cost of patients decreased from 188.23 yuan to 180.00 yuan, and clinical satisfaction with the management and use of medical consumables has been improved. Conclusion 6S management combined with the launch of 5G smart hospital logistics mode forms a new management model of clinical nursing unit medical consumables secondary warehouse, improving the timeliness, accuracy and security of medical consumables operation data.

Objective To compare the effects of spectral single energy combined with model-based adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) at a fixed 100 keV on the image quality and radiation dose of the abdominal aorta. Methods Abdominal enhancement scans patients performed in The Third Affiliated Hospital of Qiqihar Medical University from December 2022 to December 2023 were retrospectively collected. The patients were divided into two groups according to the scanning technique they received, namely the conventional group (100 keV, DLIR-H) and the spectroscopic group (80/140 keV, ASIR-V 40%). In the conventional group, DLIR-H, DLIR-M, DLIR-L, ASIR-V 40%, ASIR-V 60%, and ASIR-V 80% were reconstructed. Using the energy spectral analysis software GSI Volume Viewer, the original data were reconstructed with two levels of ASIR-V 60% and ASIR-V 80%, and the images of 40~90 keV were reconstructed at 10 keV intervals on the three ASIR-V levels, and 19 groups of images were composed together with the 120 kVp-like mixed energy images. By comparing the standard deviation (SD), signal to noise ratio (SNR) and contrast to noise ratio (CNR) of each group of images, the optimal single energy group was obtained. Results There were no statistically significant difference in SD, SNR and CNR between 60 keV combined with ASIR-V 60% compared with 120 kVp-like (P>0.05). There were no statistically significant differences in SNR, CNR and subjective scores between 60 keV combined with ASIR-V 60% compared with the conventional group (P>0.05), and the radiation dose and SD in the conventional group was lower and the difference was statistically significant (P<0.05). Conclusion DLIR-H at 100 keV can meet the diagnostic requirements of the abdominal aorta while reducing the radiation dose. Relatively speaking, it is the optimal reconstruction algorithm of the abdominal aorta. 60 keV combined with ASIR-V 60% is the best combination of single energy and reconstruction grade for abdominal aorta reconstruction.

Objective To investigate the effects of PD-1 targeted nano delivery system on the activity of gastric cancer cells and T cell immune response factors. Methods Gastric cancer cells were taken and divided into three groups, including blank control group, PD-1 inhibitor group and PD-1 targeting group. PD-1 targeted nano delivery system was prepared by emulsion solvent evaporation method. Transfection was observed under inverted fluorescence microscope, cell proliferation was detected by MTT method, cell apoptosis was detected by flow cytometry, and T cell immune response factor expression was detected by real-time PCR and western blot. Results Compared with blank control group, the transfection rate and apoptosis rate of PD-1 inhibitor group and PD-1 targeted group was increased successively, and the differences were statistically significant (P<0.05). Compared with blank control group, the cell proliferation rate of PD-1 inhibitor group and PD-1 targeted group was significantly decreased successively, and the differences were statistically significant (P<0.05). Compared with blank control group, the mRNA expressions and protein expressions of INF-γ, IL-2 and CD80 in PD-1 inhibitor group and PD-1-targeted group were increased successively, while the mRNA expressions and protein expressions of TNF-α, TGF-β1 and PD-1 were decreased successively, and the differences were statistically significant (P<0.05). Conclusion PD-1 targeted nano delivery system can efficiently deliver PD-1 inhibitors to gastric cancer cells, and effectively improve cell activity and regulate the expression of T cell immune response factors, which can provide new ideas and directions for further research and clinical application in the field of gastric cancer treatment.

Radiotherapy is one of the important comprehensive treatments for tumors. Currently, it has developed into the precision radiotherapy stage, but there are problems such as uneven distribution of medical resources, differences in level among doctors, long time spent in delineating the radiotherapy contour, human factors influencing planning design and image-guided registration, human factors influencing planning design and image-guided registration. In order to adapt to the development of the times, it is necessary to explore and try to develop intelligent radiotherapy. The increasing development of artificial intelligence technology provides a new method for realizing intelligent radiotherapy. Deep learning (DL) technology has a significant effect on graphics processing and output, which has natural advantages in the graphics processing requirements and radiotherapy process in the field of radiotherapy. Intelligent radiotherapy can promote the development of intelligent radiotherapy towards precision and personalized directions. This study reviewed the application status and development trend of DL in the process of intelligent radiotherapy for tumors.

Predictive maintenance (PdM) represents an integrated strategy for maintenance that encompasses machine status monitoring, fault diagnosis, fault prediction, and maintenance scheduling. In recent years, PdM has been progressively applied to the management of medical device and effectively addresses a series of challenges that cannot be solved by traditional maintenance strategies. To help healthcare practitioners deepen their understanding of this emerging concept, this paper introduced its background from three aspects, such as the comparison between traditional maintenance strategy and PdM, the goal of PdM and the scheme of constructing PdM; the application value of PdM in the field of medical device, the system architecture of PdM, and the practical application of PdM combined with machine learning in the management of medical device, which comprehensively demonstrated the highlights of PdM in the management of medical device; the limitations of PdM in the field of medical device management were discussed, and the corresponding solution strategies were proposed, and future development of PdM in the field of medical device management was envisioned. The main challenges currently faced were summarized to provide a reference for healthcare practitioners on this emerging field.

With the continuous development and advancement of oral digital technology, dynamic navigation and surgical robots have shown great potentiality in the field of oral digital implantation. Compared with traditional freehand implantation and static guideassisted implant surgery, dynamic navigation and implant robots can provide real-time feedback on the surgical process, so that the operator can adjust the surgical plan in a timely manner to avoid damage to important anatomical structures. Dynamic navigation and implant robotics can also improve the accuracy of implant placement, resulting in favorable long-term outcomes. At present, these two technologies are increasingly widely used by implantologists in clinical practice. This paper reviewed the clinical research and advantages and disadvantages related to dynamic navigation and surgical robots for oral implantation, in order to further understand the progress of clinical research on oral digital implantation.

A multimodal nanodiagnostic system designed for the treatment of Alzheimer’s disease (AD) combines imagingguided therapy (IGT), targeted drug delivery, smart release systems, and combination therapies. It demonstrates the potential of nanotechnology to improve therapeutic precision, efficiency, and personalization of treatment. IGT utilizes key imaging technologies to ensure therapeutic precision and optimal drug delivery pathways. Targeted drug delivery systems deliver therapeutic drugs directly to the drug area of the disease by designing specific nanocarriers, greatly increasing the local concentration of therapeutic drugs and reducing systemic side effects. The smart release system automatically adjusts the release of the drug according to the progress of the disease, maximizing the efficiency of drug use. Combination therapies integrate all of the above monotherapies to provide comprehensive treatment for AD in order to achieve a comprehensive effect. This mutimodal nanodiagnostic technology not only enhances the efficiency and precision of treatment, but also provides a new strategy for the treatment of AD through its innovative early detection and personalized treatment plan. In this paper, multimodal nano diagnosis and treatment theory was integrated into AD management, and predictive treatment plan was developed according to the disease assessment of AD, so as to reduce the harm to patients.

3D printing is a technique for creating three-dimensional models and uses computer-aided design software to convert digital models into physical objects. 3D printing technology is developing rapidly, especially in the field of health care, 3D printing technology has also been continuously developed. This paper discussed the clinical application of 3D printing technology in the field of orthopedics to treat scoliosis, briefly introduced the advantages and disadvantages of 3D printing technology, and put forward its research direction and prospect, aiming to provide the following references for 3D printing technology for scoliosis.